Detection of Chickenpox Vesicles in Digital Images of Skin Lesions

JULIAN OYOLA; VIRGINIA ARROYO; ANA RUEDIN; DANIEL ACEVEDO

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (15th Iberoamerican Congress on Pattern Recognition)

Spriger-Verlag

Lugar: Heidelberg; Año: 2012; p. 583 - 590

Chickenpox is a viral disease characterized by itchy skin vesi- cles that can have severe complications in adults. A tool for automatic detection of these lesions in patients? photographs is highly desirable to help the physician in the diagnosis. In this work we design a method for detection of chickenpox skin lesions in images. It is a combination of im- age processing techniques - color transform, equalization, edge detection, circular Hough transform- and statistical tests. We obtain highly satis- factory results in the detection of chickenpox vesicles, the elimination of false detections using the Kullback Leibler divergence, and in preliminary tests for discrimination between chickenpox and herpes zoster.